How Intelligence and Awareness Can Save Your Enterprise Millions

Ever stop to think about how many applications and VMs IT
teams manage across a datacenter of storage these days? For many enterprises,
that number can reach into the thousands. Consider that for each app, IT has to
estimate the potential storage needs, then install and configure a system that is
estimated to meet demand for the life of the application. With that scale,
manually fixing problems is not an option. As a result, enterprises often end
up attempting to spend their way out of the problem, and even this is not
always effective.

At the root of this problem is the fact that applications
are not storage aware, which means they cannot differentiate which storage
systems are fast, slow, expensive, or reliable. Since traditional systems don’t
allow data to be moved between systems without interrupting application access
(outside of virtualized environments, which still requires manual intervention
to trigger a move), if the demands of an application changes beyond the
system’s design, performance can slow for all applications with data on that
storage device. DataSphere solves this problem by making application data
storage aware and enabling data to transparently move across flash, shared, and
cloud/object storage.

Storage Awareness Eliminates Unnecessary Costs

The costs of application unawareness impact top and bottom
lines, as well as business continuity. DataSphere solves a number of issues
that rack up costs for enterprises:

PROBLEM:
Migration headaches keep data stuck until retirement. As data volume and diversity
grows, IT is spending more time handling new requests. This time crunch makes
it more stressful than ever to stop other projects when fire drill problems
rise up. As a result, data typically stays on the storage where it was
initially provisioned, until retirement when IT can move data to archival
stores.

SOLUTION:
DataSphere gives application data awareness of its requirements and storage
resources and automatically remediates to ensure alignment to objectives. DataSphere gathers telemetry
(metadata) from clients that it analyzes, in real-time, against IT-defined
policies. IT can then use this information to move data intelligently and
transparently across any storage system in its global namespace, on demand. For
example, if the latency of an application’s access requests is too high,
DataSphere can move data to storage that can meet those requirements. Conversely,
other data might need capacity more than performance. To meet these demands, DataSphere
can extend the life of existing storage by moving colder data off higher tiers.

PROBLEM: Bottlenecks hinder performance. Few
applications are allotted budget for dedicated storage. When application
workloads spike beyond the capabilities of storage, the remaining applications
must endure slow performance until the storage system works through the I/O
queue. This can create a top line cost to business, particularly when it
affects customer-facing applications.

SOLUTION: DataSphere
accelerates node and aggregate system performance. DataSphere offloads
metadata operation to greatly reducing I/O queuing, while enabling applications
to access multiple storage nodes in parallel to evenly distribute workloads. In
addition, DataSphere is aware of application requirements and storage
performance. Should any application fall out of alignment with its
requirements, DataSphere transparently redistributes workloads with live data
mobility.

PROBLEM: Overprovisioning creates overspending. In
order to minimize the impact of performance bottlenecks, enterprises commonly
buy far more capacity than they need. It’s not uncommon for IT to double each
application’s expected capacity requirements. Importantly, this storage is
typically of a type that can meet an application’s peak performance need,
meaning it’s the most expensive storage the application will ever need.

SOLUTION: DataSphere gives IT comprehensive visibility
into all storage resources and the ability to deploy new resources in minutes.
This enables enterprises to greatly reduce the amount of overprovisioning
required to protect business.

PROBLEM: Cold data hogs hot capacity, inflating the amount
of performance storage companies require. While overprovisioning capacity
is costly, so is storing cold data on Tier 1 storage. Studies have found that about 75 percent of data stored is
typically inactive,
or cold, meaning up to three fourths of storage capacity is being used
inefficiently.

SOLUTION:
DataSphere can automatically detect data that is cold and move it to more cost-effective
storage.
This ensures the most expensive storage resources are used for data that
requires those capabilities. Organizations can recognize and immediate ROI on
their existing investments, while greatly increasing the utility of new
purchases. Enterprises have reported that moving cold data off their Tier 1
systems could save them millions on their next major storage upgrade.

With DataSphere, enterprises can finally make application
data storage aware, while automating data placement, transparently, across all
available infrastructure. This improves service levels for all applications,
while reducing costs by ensuring that data is placed on the ideal storage for
its needs.

In addition, IT can stop spending time planning and moving
data around. Instead of designing fixed systems for each application and
running fire drills when plans go awry, they can create policies that define
business objectives and let DataSphere handle the movement and placement of
data. IT can even create tiered service catalogs that enable business owners to
set application service levels on their own – with the ability to see the cost
of their choices.

Want to learn more about how DataSphere can make migrations
seamless, accelerate performance of your existing storage, cut costs, and
increase Tier 1 storage utilization? Visit the DataSphere product page
or connect with us at deepdive@primarydata.com
to schedule a meeting or demo.